Overview

Dataset statistics

Number of variables18
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory70.4 KiB
Average record size in memory144.3 B

Variable types

NUM17
CAT1

Warnings

T(C) has constant value "500" Constant
Vol(aq) is highly correlated with b(H2O)High correlation
b(H2O) is highly correlated with Vol(aq)High correlation
nCa(s) is highly correlated with b(CaO)High correlation
b(CaO) is highly correlated with nCa(s)High correlation
nSi(s_reac) is highly correlated with b(SiO2)High correlation
b(SiO2) is highly correlated with nSi(s_reac)High correlation
nCa(CSHQ) is highly correlated with mCSHQ and 2 other fieldsHigh correlation
mCSHQ is highly correlated with nCa(CSHQ) and 3 other fieldsHigh correlation
nSi(CSHQ) is highly correlated with mCSHQHigh correlation
nH2O(CSHQ) is highly correlated with mCSHQ and 2 other fieldsHigh correlation
C/S(CSHQ) is highly correlated with pHHigh correlation
pH is highly correlated with C/S(CSHQ)High correlation
nGelPW(CSH) is highly correlated with mCSHQ and 2 other fieldsHigh correlation
b(CaO) has unique values Unique
b(SiO2) has unique values Unique
b(H2O) has unique values Unique
Vol(aq) has unique values Unique
nCa(aq) has unique values Unique
nCa(s) has unique values Unique
nSi(aq) has unique values Unique
nSi(s_reac) has unique values Unique
mCSHQ has unique values Unique
nCa(CSHQ) has unique values Unique
nSi(CSHQ) has unique values Unique
nH2O(CSHQ) has unique values Unique
nGelPW(CSH) has unique values Unique
nPortlandite has 189 (37.8%) zeros Zeros
nAmor-Sl has 443 (88.6%) zeros Zeros

Reproduction

Analysis started2022-11-01 15:08:52.603117
Analysis finished2022-11-01 15:10:31.550950
Duration1 minute and 38.95 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

T(C)
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
25
500 
ValueCountFrequency (%) 
25500100.0%
 
2022-11-01T10:10:31.758963image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2022-11-01T10:10:31.887923image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:32.028560image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length4
Min length4

b(CaO)
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9499761384
Minimum0.1028776
Maximum1.798218
Zeros0
Zeros (%)0.0%
Memory size3.9 KiB
2022-11-01T10:10:32.262946image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.1028776
5-th percentile0.18807164
Q10.527274925
median0.94944105
Q31.37412275
95-th percentile1.7146575
Maximum1.798218
Range1.6953404
Interquartile range (IQR)0.846847825

Descriptive statistics

Standard deviation0.4912521308
Coefficient of variation (CV)0.5171204948
Kurtosis-1.199804629
Mean0.9499761384
Median Absolute Deviation (MAD)0.42396255
Skewness0.0002439898225
Sum474.9880692
Variance0.241328656
MonotocityNot monotonic
2022-11-01T10:10:32.544177image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.57079510.2%
 
0.131352610.2%
 
1.4410810.2%
 
0.748493910.2%
 
0.631287210.2%
 
1.13432710.2%
 
0.574273210.2%
 
1.4092610.2%
 
1.03442210.2%
 
0.783239110.2%
 
Other values (490)49098.0%
 
ValueCountFrequency (%) 
0.102877610.2%
 
0.105322410.2%
 
0.107835710.2%
 
0.110878910.2%
 
0.114970310.2%
 
ValueCountFrequency (%) 
1.79821810.2%
 
1.7947110.2%
 
1.79228510.2%
 
1.78874210.2%
 
1.78546310.2%
 

b(SiO2)
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4499993918
Minimum0.2005553
Maximum0.6994621
Zeros0
Zeros (%)0.0%
Memory size3.9 KiB
2022-11-01T10:10:33.716348image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.2005553
5-th percentile0.225498485
Q10.3253549
median0.4499881
Q30.575021325
95-th percentile0.674105275
Maximum0.6994621
Range0.4989068
Interquartile range (IQR)0.249666425

Descriptive statistics

Standard deviation0.1444680127
Coefficient of variation (CV)0.321040462
Kurtosis-1.200555569
Mean0.4499993918
Median Absolute Deviation (MAD)0.12512425
Skewness-0.0003019458626
Sum224.9996959
Variance0.02087100668
MonotocityNot monotonic
2022-11-01T10:10:34.059689image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.393695810.2%
 
0.546419610.2%
 
0.309295110.2%
 
0.371163510.2%
 
0.436188710.2%
 
0.440809710.2%
 
0.495363110.2%
 
0.595902510.2%
 
0.60784610.2%
 
0.547065110.2%
 
Other values (490)49098.0%
 
ValueCountFrequency (%) 
0.200555310.2%
 
0.201998510.2%
 
0.202261410.2%
 
0.203848610.2%
 
0.204212610.2%
 
ValueCountFrequency (%) 
0.699462110.2%
 
0.698467110.2%
 
0.69748710.2%
 
0.696884410.2%
 
0.695337710.2%
 

b(H2O)
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.551047142
Minimum2.777311
Maximum8.323656
Zeros0
Zeros (%)0.0%
Memory size3.9 KiB
2022-11-01T10:10:34.403446image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum2.777311
5-th percentile3.0572542
Q14.16790075
median5.550264
Q36.93334475
95-th percentile8.04790445
Maximum8.323656
Range5.546345
Interquartile range (IQR)2.765444

Descriptive statistics

Standard deviation1.604008135
Coefficient of variation (CV)0.2889559562
Kurtosis-1.199974382
Mean5.551047142
Median Absolute Deviation (MAD)1.3862865
Skewness0.0003006774355
Sum2775.523571
Variance2.572842097
MonotocityNot monotonic
2022-11-01T10:10:34.733975image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
7.25589110.2%
 
6.1031810.2%
 
5.38002910.2%
 
5.15223910.2%
 
3.31914510.2%
 
5.22692510.2%
 
5.79885510.2%
 
8.00438810.2%
 
7.68943410.2%
 
4.11088110.2%
 
Other values (490)49098.0%
 
ValueCountFrequency (%) 
2.77731110.2%
 
2.79035110.2%
 
2.80331210.2%
 
2.81547710.2%
 
2.82830110.2%
 
ValueCountFrequency (%) 
8.32365610.2%
 
8.31410910.2%
 
8.2993110.2%
 
8.28858110.2%
 
8.27166710.2%
 

Vol(aq)
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07420627147
Minimum0.004780485
Maximum0.1457335
Zeros0
Zeros (%)0.0%
Memory size3.9 KiB
2022-11-01T10:10:35.062735image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.004780485
5-th percentile0.0242632185
Q10.049568975
median0.074569565
Q30.099372375
95-th percentile0.12274353
Maximum0.1457335
Range0.140953015
Interquartile range (IQR)0.0498034

Descriptive statistics

Standard deviation0.03080475184
Coefficient of variation (CV)0.4151232938
Kurtosis-0.9394573036
Mean0.07420627147
Median Absolute Deviation (MAD)0.024916145
Skewness-0.01559997737
Sum37.10313574
Variance0.0009489327356
MonotocityNot monotonic
2022-11-01T10:10:35.437725image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.0937803510.2%
 
0.104946110.2%
 
0.0641510610.2%
 
0.0711476310.2%
 
0.0392853610.2%
 
0.0639545810.2%
 
0.0847550910.2%
 
0.105647310.2%
 
0.106458910.2%
 
0.0485467310.2%
 
Other values (490)49098.0%
 
ValueCountFrequency (%) 
0.00478048510.2%
 
0.011886110.2%
 
0.0124148310.2%
 
0.0138779210.2%
 
0.0145510510.2%
 
ValueCountFrequency (%) 
0.145733510.2%
 
0.141580310.2%
 
0.138889610.2%
 
0.137081310.2%
 
0.133606910.2%
 

pH
Real number (ℝ≥0)

HIGH CORRELATION

Distinct142
Distinct (%)28.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.97419977
Minimum9.793652
Maximum12.47262
Zeros0
Zeros (%)0.0%
Memory size3.9 KiB
2022-11-01T10:10:35.785308image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum9.793652
5-th percentile9.793655
Q111.9101175
median12.47261
Q312.47261
95-th percentile12.47261
Maximum12.47262
Range2.678968
Interquartile range (IQR)0.5624925

Descriptive statistics

Standard deviation0.8926673847
Coefficient of variation (CV)0.074549231
Kurtosis1.450805535
Mean11.97419977
Median Absolute Deviation (MAD)0
Skewness-1.72667454
Sum5987.099885
Variance0.7968550596
MonotocityNot monotonic
2022-11-01T10:10:36.160980image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
12.4726131062.0%
 
9.793655275.4%
 
9.79365791.8%
 
9.79365361.2%
 
9.79365840.8%
 
9.79365640.8%
 
9.79365440.8%
 
9.79365920.4%
 
11.2996710.2%
 
11.8419910.2%
 
Other values (132)13226.4%
 
ValueCountFrequency (%) 
9.79365210.2%
 
9.79365361.2%
 
9.79365440.8%
 
9.793655275.4%
 
9.79365640.8%
 
ValueCountFrequency (%) 
12.4726210.2%
 
12.4726131062.0%
 
12.4515810.2%
 
12.4454110.2%
 
12.4374110.2%
 

nCa(aq)
Real number (ℝ≥0)

UNIQUE

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.001012704559
Minimum3.167933e-05
Maximum0.00259823
Zeros0
Zeros (%)0.0%
Memory size3.9 KiB
2022-11-01T10:10:36.489110image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum3.167933e-05
5-th percentile6.45274505e-05
Q10.000303659875
median0.0009223634
Q30.00163096525
95-th percentile0.00227670535
Maximum0.00259823
Range0.00256655067
Interquartile range (IQR)0.001327305375

Descriptive statistics

Standard deviation0.0007503648347
Coefficient of variation (CV)0.7409513744
Kurtosis-1.137075849
Mean0.001012704559
Median Absolute Deviation (MAD)0.0006674301
Skewness0.3320024338
Sum0.5063522794
Variance5.630473852e-07
MonotocityNot monotonic
2022-11-01T10:10:36.843845image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.00190078810.2%
 
0.000110130210.2%
 
0.00130026910.2%
 
0.00144205710.2%
 
0.000473739910.2%
 
0.00129626410.2%
 
0.000354385710.2%
 
0.00214131210.2%
 
0.00215776510.2%
 
0.000556243610.2%
 
Other values (490)49098.0%
 
ValueCountFrequency (%) 
3.167933e-0510.2%
 
3.362566e-0510.2%
 
3.989865e-0510.2%
 
4.289694e-0510.2%
 
4.636751e-0510.2%
 
ValueCountFrequency (%) 
0.0025982310.2%
 
0.00259735610.2%
 
0.00254895910.2%
 
0.00254795210.2%
 
0.00253911910.2%
 

nCa(s)
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.948963434
Minimum0.1028196
Maximum1.797213
Zeros0
Zeros (%)0.0%
Memory size3.9 KiB
2022-11-01T10:10:37.171977image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.1028196
5-th percentile0.187961355
Q10.52596155
median0.9478251
Q31.37284225
95-th percentile1.71355545
Maximum1.797213
Range1.6943934
Interquartile range (IQR)0.8468807

Descriptive statistics

Standard deviation0.4909062361
Coefficient of variation (CV)0.5173078524
Kurtosis-1.19956056
Mean0.948963434
Median Absolute Deviation (MAD)0.42371095
Skewness0.001917153528
Sum474.481717
Variance0.2409889326
MonotocityNot monotonic
2022-11-01T10:10:37.468854image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.56889410.2%
 
0.131242510.2%
 
1.4397810.2%
 
0.747051810.2%
 
0.630813510.2%
 
1.13303110.2%
 
0.573918810.2%
 
1.40711910.2%
 
1.03226410.2%
 
0.782682910.2%
 
Other values (490)49098.0%
 
ValueCountFrequency (%) 
0.102819610.2%
 
0.105193710.2%
 
0.107753310.2%
 
0.11077310.2%
 
0.114817410.2%
 
ValueCountFrequency (%) 
1.79721310.2%
 
1.79402210.2%
 
1.79163410.2%
 
1.78701710.2%
 
1.78455510.2%
 

nSi(aq)
Real number (ℝ≥0)

UNIQUE

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.920995458e-05
Minimum1.477955e-07
Maximum0.0005742409
Zeros0
Zeros (%)0.0%
Memory size3.9 KiB
2022-11-01T10:10:37.799010image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1.477955e-07
5-th percentile7.5013155e-07
Q11.798547e-06
median2.960199e-06
Q31.17220025e-05
95-th percentile0.000387992035
Maximum0.0005742409
Range0.0005740931045
Interquartile range (IQR)9.9234555e-06

Descriptive statistics

Standard deviation0.0001189638366
Coefficient of variation (CV)2.417475034
Kurtosis6.773167282
Mean4.920995458e-05
Median Absolute Deviation (MAD)1.5812195e-06
Skewness2.78099332
Sum0.02460497729
Variance1.415239443e-08
MonotocityNot monotonic
2022-11-01T10:10:38.109816image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
2.899352e-0610.2%
 
0.00041353510.2%
 
1.983318e-0610.2%
 
2.199623e-0610.2%
 
2.440934e-0610.2%
 
1.977248e-0610.2%
 
1.531763e-0510.2%
 
3.266203e-0610.2%
 
3.291318e-0610.2%
 
3.203564e-0610.2%
 
Other values (490)49098.0%
 
ValueCountFrequency (%) 
1.477955e-0710.2%
 
3.67474e-0710.2%
 
3.838218e-0710.2%
 
4.290542e-0710.2%
 
4.498663e-0710.2%
 
ValueCountFrequency (%) 
0.000574240910.2%
 
0.000557865910.2%
 
0.000547233410.2%
 
0.000540218510.2%
 
0.000526399310.2%
 

nSi(s_reac)
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4499501834
Minimum0.2005458
Maximum0.6994614
Zeros0
Zeros (%)0.0%
Memory size3.9 KiB
2022-11-01T10:10:38.422316image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.2005458
5-th percentile0.225496295
Q10.325353425
median0.4499664
Q30.574728575
95-th percentile0.674093035
Maximum0.6994614
Range0.4989156
Interquartile range (IQR)0.24937515

Descriptive statistics

Standard deviation0.1444383316
Coefficient of variation (CV)0.3210096072
Kurtosis-1.200507462
Mean0.4499501834
Median Absolute Deviation (MAD)0.12493105
Skewness-0.0003734359676
Sum224.9750917
Variance0.02086243164
MonotocityNot monotonic
2022-11-01T10:10:38.759372image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.393692910.2%
 
0.546006110.2%
 
0.309293110.2%
 
0.371161310.2%
 
0.436186310.2%
 
0.440807710.2%
 
0.495347810.2%
 
0.595899210.2%
 
0.607842710.2%
 
0.547061910.2%
 
Other values (490)49098.0%
 
ValueCountFrequency (%) 
0.200545810.2%
 
0.201997510.2%
 
0.202251910.2%
 
0.203846110.2%
 
0.204209210.2%
 
ValueCountFrequency (%) 
0.699461410.2%
 
0.698448410.2%
 
0.697051710.2%
 
0.696883110.2%
 
0.695336610.2%
 

nPortlandite
Real number (ℝ≥0)

ZEROS

Distinct312
Distinct (%)62.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3544796417
Minimum0
Maximum1.401833
Zeros189
Zeros (%)37.8%
Memory size3.9 KiB
2022-11-01T10:10:39.062294image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.20125475
Q30.6586107
95-th percentile1.1065208
Maximum1.401833
Range1.401833
Interquartile range (IQR)0.6586107

Descriptive statistics

Standard deviation0.390830867
Coefficient of variation (CV)1.102548132
Kurtosis-0.6673187004
Mean0.3544796417
Median Absolute Deviation (MAD)0.20125475
Skewness0.7762747068
Sum177.2398209
Variance0.1527487666
MonotocityNot monotonic
2022-11-01T10:10:39.421691image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
018937.8%
 
0.143164810.2%
 
0.415827510.2%
 
0.437578410.2%
 
0.0432916610.2%
 
0.254970510.2%
 
0.831271410.2%
 
1.08407910.2%
 
0.753861510.2%
 
0.296175110.2%
 
Other values (302)30260.4%
 
ValueCountFrequency (%) 
018937.8%
 
0.0137464710.2%
 
0.0161042310.2%
 
0.0205708810.2%
 
0.0244616710.2%
 
ValueCountFrequency (%) 
1.40183310.2%
 
1.34166110.2%
 
1.33166310.2%
 
1.32695110.2%
 
1.28839910.2%
 

nAmor-Sl
Real number (ℝ≥0)

ZEROS

Distinct58
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02398505199
Minimum0
Maximum0.5327833
Zeros443
Zeros (%)88.6%
Memory size3.9 KiB
2022-11-01T10:10:39.763013image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.22921646
Maximum0.5327833
Range0.5327833
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.08160764784
Coefficient of variation (CV)3.402437813
Kurtosis14.52497388
Mean0.02398505199
Median Absolute Deviation (MAD)0
Skewness3.80732093
Sum11.99252599
Variance0.006659808186
MonotocityNot monotonic
2022-11-01T10:10:40.156376image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
044388.6%
 
0.33859810.2%
 
0.108225610.2%
 
0.185485210.2%
 
0.100366510.2%
 
0.0108374210.2%
 
0.0167421510.2%
 
0.283745710.2%
 
0.160225110.2%
 
0.28214510.2%
 
Other values (48)489.6%
 
ValueCountFrequency (%) 
044388.6%
 
0.00909502510.2%
 
0.0108374210.2%
 
0.0121567110.2%
 
0.0167421510.2%
 
ValueCountFrequency (%) 
0.532783310.2%
 
0.500443310.2%
 
0.466853210.2%
 
0.444937410.2%
 
0.433533210.2%
 

mCSHQ
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07852066286
Minimum0.01908214
Maximum0.1421112
Zeros0
Zeros (%)0.0%
Memory size3.9 KiB
2022-11-01T10:10:40.468950image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.01908214
5-th percentile0.0328746865
Q10.05504434
median0.075552875
Q30.101542625
95-th percentile0.13068288
Maximum0.1421112
Range0.12302906
Interquartile range (IQR)0.046498285

Descriptive statistics

Standard deviation0.02952364454
Coefficient of variation (CV)0.3759984119
Kurtosis-0.8177565491
Mean0.07852066286
Median Absolute Deviation (MAD)0.0228302
Skewness0.185626681
Sum39.26033143
Variance0.0008716455867
MonotocityNot monotonic
2022-11-01T10:10:40.811150image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.0799875110.2%
 
0.024357110.2%
 
0.0628398110.2%
 
0.0754097110.2%
 
0.082188410.2%
 
0.0895599410.2%
 
0.0818937110.2%
 
0.121070210.2%
 
0.123496810.2%
 
0.102392510.2%
 
Other values (490)49098.0%
 
ValueCountFrequency (%) 
0.0190821410.2%
 
0.0195227510.2%
 
0.0199977910.2%
 
0.020558210.2%
 
0.0213087910.2%
 
ValueCountFrequency (%) 
0.142111210.2%
 
0.141273210.2%
 
0.141092910.2%
 
0.139814410.2%
 
0.139632810.2%
 

nCa(CSHQ)
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5944837944
Minimum0.1028196
Maximum1.138038
Zeros0
Zeros (%)0.0%
Memory size3.9 KiB
2022-11-01T10:10:41.156778image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.1028196
5-th percentile0.187961355
Q10.401986825
median0.56779165
Q30.786385875
95-th percentile1.0427138
Maximum1.138038
Range1.0352184
Interquartile range (IQR)0.38439905

Descriptive statistics

Standard deviation0.2535459238
Coefficient of variation (CV)0.4264976207
Kurtosis-0.7873673563
Mean0.5944837944
Median Absolute Deviation (MAD)0.1897247
Skewness0.1811800864
Sum297.2418972
Variance0.06428553549
MonotocityNot monotonic
2022-11-01T10:10:41.484909image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.640546410.2%
 
0.131242510.2%
 
0.503226310.2%
 
0.603887110.2%
 
0.630813510.2%
 
0.717203210.2%
 
0.573918810.2%
 
0.969540310.2%
 
0.988972610.2%
 
0.782682910.2%
 
Other values (490)49098.0%
 
ValueCountFrequency (%) 
0.102819610.2%
 
0.105193710.2%
 
0.107753310.2%
 
0.11077310.2%
 
0.114817410.2%
 
ValueCountFrequency (%) 
1.13803810.2%
 
1.13132710.2%
 
1.12988410.2%
 
1.11964510.2%
 
1.1181910.2%
 

nSi(CSHQ)
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4259651312
Minimum0.1523485
Maximum0.6994614
Zeros0
Zeros (%)0.0%
Memory size3.9 KiB
2022-11-01T10:10:41.833306image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.1523485
5-th percentile0.213302365
Q10.299462475
median0.4150915
Q30.551139925
95-th percentile0.6643878
Maximum0.6994614
Range0.5471129
Interquartile range (IQR)0.25167745

Descriptive statistics

Standard deviation0.1461435268
Coefficient of variation (CV)0.3430880044
Kurtosis-1.141431174
Mean0.4259651312
Median Absolute Deviation (MAD)0.1240926
Skewness0.1339147738
Sum212.9825656
Variance0.02135793042
MonotocityNot monotonic
2022-11-01T10:10:42.157388image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.393692910.2%
 
0.194462810.2%
 
0.309293110.2%
 
0.371161310.2%
 
0.436186310.2%
 
0.440807710.2%
 
0.495347810.2%
 
0.595899210.2%
 
0.607842710.2%
 
0.547061910.2%
 
Other values (490)49098.0%
 
ValueCountFrequency (%) 
0.152348510.2%
 
0.155866210.2%
 
0.159658910.2%
 
0.164133110.2%
 
0.170125710.2%
 
ValueCountFrequency (%) 
0.699461410.2%
 
0.698448410.2%
 
0.696883110.2%
 
0.695336610.2%
 
0.694449510.2%
 

nH2O(CSHQ)
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.087394708
Minimum0.2310555
Maximum2.013086
Zeros0
Zeros (%)0.0%
Memory size3.9 KiB
2022-11-01T10:10:42.469886image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.2310555
5-th percentile0.41811763
Q10.75348175
median1.047014
Q31.420889
95-th percentile1.8446082
Maximum2.013086
Range1.7820305
Interquartile range (IQR)0.66740725

Descriptive statistics

Standard deviation0.4290504316
Coefficient of variation (CV)0.3945673346
Kurtosis-0.7863024137
Mean1.087394708
Median Absolute Deviation (MAD)0.3240346
Skewness0.1892953696
Sum543.697354
Variance0.1840842728
MonotocityNot monotonic
2022-11-01T10:10:42.858951image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.13306910.2%
 
0.294927310.2%
 
0.890161710.2%
 
1.06822210.2%
 
1.1438110.2%
 
1.26866810.2%
 
1.10723710.2%
 
1.71502910.2%
 
1.74940310.2%
 
1.42278210.2%
 
Other values (490)49098.0%
 
ValueCountFrequency (%) 
0.231055510.2%
 
0.236390710.2%
 
0.242142610.2%
 
0.248928410.2%
 
0.258016910.2%
 
ValueCountFrequency (%) 
2.01308610.2%
 
2.00121510.2%
 
1.99866210.2%
 
1.98055110.2%
 
1.97797810.2%
 

C/S(CSHQ)
Real number (ℝ≥0)

HIGH CORRELATION

Distinct138
Distinct (%)27.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.39192024
Minimum0.6748971
Maximum1.627021
Zeros0
Zeros (%)0.0%
Memory size3.9 KiB
2022-11-01T10:10:43.218335image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.6748971
5-th percentile0.6748972
Q11.202726
median1.627021
Q31.627021
95-th percentile1.627021
Maximum1.627021
Range0.9521239
Interquartile range (IQR)0.424295

Descriptive statistics

Standard deviation0.3586934423
Coefficient of variation (CV)0.2576968363
Kurtosis-0.3479452379
Mean1.39192024
Median Absolute Deviation (MAD)0
Skewness-1.158195877
Sum695.9601201
Variance0.1286609855
MonotocityNot monotonic
2022-11-01T10:10:43.562074image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.62702127254.4%
 
1.62702397.8%
 
0.6748973275.4%
 
0.6748972265.2%
 
0.674897430.6%
 
0.715069210.2%
 
0.829912110.2%
 
1.41384310.2%
 
1.59179110.2%
 
1.28614210.2%
 
Other values (128)12825.6%
 
ValueCountFrequency (%) 
0.674897110.2%
 
0.6748972265.2%
 
0.6748973275.4%
 
0.674897430.6%
 
0.678171910.2%
 
ValueCountFrequency (%) 
1.62702127254.4%
 
1.62702397.8%
 
1.6058210.2%
 
1.59968610.2%
 
1.59179110.2%
 

nGelPW(CSH)
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4482009469
Minimum0.07894314
Maximum0.8609357
Zeros0
Zeros (%)0.0%
Memory size3.9 KiB
2022-11-01T10:10:43.906510image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.07894314
5-th percentile0.14439986
Q10.30554985
median0.4281641
Q30.593255175
95-th percentile0.786086605
Maximum0.8609357
Range0.78199256
Interquartile range (IQR)0.287705325

Descriptive statistics

Standard deviation0.1905147575
Coefficient of variation (CV)0.4250654953
Kurtosis-0.7550960826
Mean0.4482009469
Median Absolute Deviation (MAD)0.1413507
Skewness0.2023117595
Sum224.1004734
Variance0.03629587282
MonotocityNot monotonic
2022-11-01T10:10:44.265893image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.484578910.2%
 
0.100765810.2%
 
0.38069510.2%
 
0.456845810.2%
 
0.467869910.2%
 
0.542570410.2%
 
0.411468810.2%
 
0.733465610.2%
 
0.748166310.2%
 
0.578637110.2%
 
Other values (490)49098.0%
 
ValueCountFrequency (%) 
0.0789431410.2%
 
0.0807659710.2%
 
0.0827311810.2%
 
0.0850496710.2%
 
0.0881548710.2%
 
ValueCountFrequency (%) 
0.860935710.2%
 
0.855858610.2%
 
0.854766710.2%
 
0.847021210.2%
 
0.845920810.2%
 

Interactions

2022-11-01T10:09:03.455282image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:03.811532image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:04.072133image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:04.336330image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:04.618330image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:04.913346image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:05.240904image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:05.537966image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:05.824764image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:06.129075image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:06.457078image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:06.803082image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:07.103226image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:07.400227image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:07.674828image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:07.975397image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:08.237891image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:08.506550image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:08.800983image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:09.115797image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:09.365804image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:09.694301image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:09.990772image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:10.584551image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:10.856370image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:11.147022image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:11.443288image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:11.732961image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:12.026622image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:12.323849image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:12.590707image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:12.866119image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:13.178281image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:13.437133image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:13.725585image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:13.984949image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:14.240899image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:14.516118image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:14.807038image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:15.106350image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:15.381478image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:15.682670image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:15.985284image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:16.287915image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:16.600679image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:16.923308image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:17.209639image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:17.516568image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:17.803444image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:18.084564image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:18.334884image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:18.616040image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:18.912837image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:19.234264image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:19.566255image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:19.897254image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:20.368392image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:20.673371image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:21.356109image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:21.731468image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:22.033459image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:22.350542image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:22.678320image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:22.975462image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:23.291107image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:23.601345image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:24.006858image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:24.292965image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:24.600294image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:25.319022image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:25.631593image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:25.912721image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:26.225718image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:26.510723image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:26.807737image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:27.100891image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:27.381573image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:27.631719image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:27.944334image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:28.225671image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:28.475297image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:28.749400image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:28.991145image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:29.303406image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:29.600258image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:29.865918image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:30.156523image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:30.412813image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:30.647199image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:30.944342image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:31.222448image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:31.490894image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:31.795494image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:32.271098image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:32.709688image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:33.116033image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:33.409756image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:33.709731image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:34.053870image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:34.334723image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:34.616208image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:35.272375image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:35.569938image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:35.851392image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:36.162875image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:36.428482image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:36.762307image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:37.024748image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:37.303477image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:37.609327image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:37.975396image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:38.303761image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:38.569129image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:38.851431image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:39.154861image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:39.412857image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:39.693787image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:40.006676image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:40.285314image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
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2022-11-01T10:09:40.866576image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:41.162877image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:41.444501image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:41.764346image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:42.037916image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:42.319177image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:42.600413image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:42.906622image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:43.178526image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:43.481308image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:43.767386image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:44.096066image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:44.366029image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:44.647599image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:44.944451image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:45.225431image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:45.533025image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:45.829629image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:46.113943image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:46.350535image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:46.628105image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:46.897370image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:47.186299image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:47.475445image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:47.777466image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:48.053525image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:48.366142image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:48.647310image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:48.944440image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:49.222396image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:49.491096image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:49.785483image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:50.053526image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:50.369729image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:51.147357image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:51.453223image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:51.725536image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:52.037960image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:52.303603image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:52.585091image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:52.917717image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:53.209877image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:53.502651image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:53.814712image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:54.100835image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:54.459841image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:54.747555image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:55.057626image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:55.350518image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:55.662489image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:55.959924image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:56.241157image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:56.491137image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:56.745651image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:57.006744image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:57.269687image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:57.522396image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:57.789238image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:58.053635image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:58.335215image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:58.600505image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:58.891503image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:59.194284image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:59.459908image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:59.709868image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:09:59.975764image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:00.209907image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:00.491472image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:00.764319image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:01.008220image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:01.288029image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:01.616179image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:01.897709image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:02.178678image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:02.473686image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:02.750548image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:03.026482image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:03.319434image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:03.631616image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:03.913031image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:04.212265image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:04.522441image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:04.851213image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:05.123858image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:05.413065image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:05.671888image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:05.928699image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:06.204271image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:06.491225image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:06.753562image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:07.038171image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:07.336439image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:07.631838image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:07.903306image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:08.178725image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:08.444632image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:08.709935image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:08.991367image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:09.272443image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:09.553778image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:10.477625image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:10.742733image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:11.016514image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:11.288110image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:11.567449image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:11.851215image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:12.132840image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:12.413178image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:12.709987image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:12.991254image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:13.257302image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:13.538103image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:13.832498image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:14.085001image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:14.413460image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:14.686719image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:14.975713image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:15.234335image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:15.506910image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:15.823926image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:16.116256image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:16.381930image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:16.663126image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:16.944421image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:17.225635image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:17.522566image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:17.870754image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:18.163172image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:18.491379image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:18.783392image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:19.069440image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:19.366270image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:19.678849image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:19.996255image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:20.272527image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:20.586391image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:20.851442image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:21.116781image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:21.382082image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:21.648639image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:21.932052image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:22.225972image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:22.547895image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:22.837085image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:23.085035image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:23.429403image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:23.663780image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:23.962014image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:24.180784image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:24.460798image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:24.745572image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:24.992949image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:25.258594image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:25.571100image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:25.835939image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:26.117197image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:26.445328image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:26.726587image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:27.024135image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:27.305367image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:27.586625image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:27.867286image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:28.148525image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:28.414155image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:28.711027image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:29.007975image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:29.304832image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:29.586072image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:29.835100image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Correlations

2022-11-01T10:10:44.652976image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-11-01T10:10:45.230229image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-11-01T10:10:45.840099image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-11-01T10:10:46.433855image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-11-01T10:10:30.499929image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2022-11-01T10:10:31.228882image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Sample

First rows

T(C)b(CaO)b(SiO2)b(H2O)Vol(aq)pHnCa(aq)nCa(s)nSi(aq)nSi(s_reac)nPortlanditenAmor-SlmCSHQnCa(CSHQ)nSi(CSHQ)nH2O(CSHQ)C/S(CSHQ)nGelPW(CSH)
025.01.5707950.3936967.2558910.09378012.472610.0019011.5688942.899352e-060.3936930.9283480.00.0799880.6405460.3936931.1330691.6270210.484579
125.00.6715360.4770987.3213680.11012212.218500.0011570.6703798.028254e-060.4770900.0000000.00.0883090.6703790.4770901.2239581.4051410.492938
225.00.3750900.2693275.8236790.09280812.196570.0009220.3741687.197989e-060.2693200.0000000.00.0495060.3741680.2693200.6850751.3893050.274215
325.00.6920740.4740022.8630430.02910112.289120.0003660.6917081.718686e-060.4740010.0000000.00.0898180.6917080.4740011.2516221.4592980.514404
425.00.9621640.2255685.0521940.06877112.472610.0013940.9607702.126388e-060.2255660.5937710.00.0458290.3670000.2255660.6491891.6270210.277639
525.01.1931300.6520772.7773110.01387812.472610.0002811.1928494.290542e-070.6520770.1319070.00.1324841.0609420.6520771.8767101.6270200.802612
625.01.4256870.5150546.3863010.07795412.472610.0015801.4241072.410088e-060.5150510.5861080.00.1046440.8379990.5150511.4823441.6270210.633953
725.00.5451850.6676507.7728790.11930111.246180.0001540.5450316.872505e-050.6675810.0000000.00.0917500.5450310.6675811.1698110.8164270.432301
825.01.7461120.3905744.5244090.04135312.472610.0008381.7452741.278467e-060.3905731.1098040.00.0793540.6354700.3905731.1240891.6270210.480739
925.00.2852680.2978513.4670410.05209511.535020.0001110.2851561.747901e-050.2978340.0000000.00.0443990.2851560.2978340.5835830.9574350.215384

Last rows

T(C)b(CaO)b(SiO2)b(H2O)Vol(aq)pHnCa(aq)nCa(s)nSi(aq)nSi(s_reac)nPortlanditenAmor-SlmCSHQnCa(CSHQ)nSi(CSHQ)nH2O(CSHQ)C/S(CSHQ)nGelPW(CSH)
49025.00.8369750.5629325.6767140.07530412.3203600.0010270.8359494.027226e-060.5629280.0000000.0000000.1078450.8359490.5629281.5066971.4850010.624759
49125.00.8679940.6030462.9538160.02489712.2632700.0002930.8677001.591621e-060.6030440.0000000.0000000.1132700.8677000.6030441.5752111.4388670.642589
49225.01.2707710.2038495.9891830.08061112.4726100.0016341.2691372.492197e-060.2038460.9374750.0000000.0414160.3316620.2038460.5866801.6270210.250905
49325.00.3128350.4356033.6624450.05362310.7764400.0000470.3127886.103023e-050.4355420.0000000.0000000.0562220.3127880.4355420.6945740.7181580.247052
49425.00.8958700.4689087.6141140.11074012.4726100.0022450.8936253.423679e-060.4689050.1307070.0000000.0952690.7629180.4689051.3495331.6270210.577154
49525.00.2312430.4391043.4117360.0522589.7936570.0000550.2311882.059216e-040.4388980.0000000.0963450.0429060.2311880.3425530.5195240.6748970.177502
49625.00.1782520.3438772.8728830.0446739.7936550.0000470.1782051.760204e-040.3437010.0000000.0796530.0330730.1782050.2640480.4004620.6748970.136823
49725.00.6054250.3460526.7611770.10335712.4726100.0020950.6033303.195438e-060.3460490.0403020.0000000.0703080.5630280.3460490.9959461.6270210.425936
49825.01.4210620.6569143.7063640.02643112.4726100.0005361.4205268.171574e-070.6569130.3517150.0000000.1334671.0688120.6569131.8906311.6270210.808565
49925.01.0385770.2643343.9119000.04592112.4726100.0009311.0376461.419709e-060.2643330.6075710.0000000.0537050.4300750.2643330.7607641.6270210.325356